Development of a decision support system for the introduction of alternative methods into local irritancy/corrosivity testing strategies. Developmentof a relational database

For new chemical substances that are notified within the European Union, da ta sets have to be submitted to the National Competent Authorities. The dat a submitted have to demonstrate the physicochemical and toxic properties of the new chemical, such as solubility, partition coefficients and spectra, as well as acute toxic properties and the potential to cause local irritant or corrosive effects. In order to minimise testing for notification purpos es (for example, animal testing), it is necessary to develop stepwise asses sment procedures, including structure-activity considerations, alternative methods (for example, in vitro tests), and computerised structure-activity relationship (SAR) models. An electronic database was developed which conta ins physicochemical and toxicological data on approximately 1300 chemical s ubstances. It is used for regulatory structure-property relationship (SPR) and SAR considerations, and for the development of rules for a decision sup port system (DSS) for the introduction of alternative methods into local ir ritancy/corrosivity testing strategies. The information stored in the datab ase is derived from proprietary data, so it is not possible to publish the data directly. Therefore, the database is evaluated by regulators, and the information derived from the data is used for the development of scientific information about SARs. This information can be published, for example, by means of tables correlating measured physicochemical values and specific t oxic effects caused by the measured chemical. This information is introduce d to the public by means of a DSS that predicts local irritant/corrosive po tential of a chemical by listing so-called exception rules of the kind IF ( physicochemical property) A THEN not (toxic) Effect B and so-called structu ral rules of the kind IF Substructure A THEN Effect B. These DSS rules "tra nslate" proprietary data into scientific knowledge that can be published.